app.py

import gradio as gr
import json
import pandas as pd

def analyze_file(message, file):
    if not file:
        return "Please upload a file."

    filepath = file.name
    filename = filepath.split("/")[-1]
    ext = filename.split(".")[-1].lower()

    try:
        # Known types
        if ext == "jsonl":
            with open(filepath, "r", encoding="utf-8") as f:
                lines = f.readlines()
                data = [json.loads(line) for line in lines]
            return f"📄 JSONL file with *{len(data)}* entries."

        elif ext == "json":
            with open(filepath, "r", encoding="utf-8") as f:
                content = json.load(f)
            if isinstance(content, dict):
                return f"📁 JSON with *{len(content.keys())}* top-level keys."
            elif isinstance(content, list):
                return f"📁 JSON with *{len(content)}* list items."
            else:
                return f"🌀 JSON with data type: {type(content)}"

        elif ext == "csv":
            df = pd.read_csv(filepath)
            return f"📊 CSV with *{df.shape[0]}* rows and *{df.shape[1]}* columns."

        elif ext == "py":
            with open(filepath, "r", encoding="utf-8") as f:
                code = f.read()
            return f"💻 Python file with *{len(code.splitlines())}* lines of code."

        # Unknown types – attempt plain text preview
        else:
            try:
                with open(filepath, "r", encoding="utf-8") as f:
                    content = f.read()
                preview = content[:1000]
                return f"📦 {ext} file preview:\n\n\n{preview}\n"
            except Exception as e:
                return f"❌ Cannot preview this {ext} file. Likely binary. Error: {e}"

    except Exception as e:
        return f"❌ Error processing file: {e}"

# Gradio interface
iface = gr.Interface(
    fn=analyze_file,
    inputs=[
        gr.Textbox(label="Message (not used yet)", placeholder="You can ask questions soon"),
        gr.File(label="Upload any file")
    ],
    outputs="text",
    title="AI Assistant – Universal File Reader",
    description="Upload any file (.json, .csv, .py, .txt, .docx, etc). I’ll preview what I can."
)

iface.launch()